2 citations · 13 across the 34 of their papers we have counts for
6 papers · 1 filter
From Classification to Generation: Insights into Crosslingual Retrieval Augmented ICL
Xiaoqian Li, Ercong Nie, Sheng Liang
The remarkable ability of Large Language Models (LLMs) to understand and follow instructions has sometimes been limited by their in-context learning (ICL) performance in low-resour…
Crosslingual Retrieval Augmented In-context Learning for Bangla
Xiaoqian Li, Ercong Nie, Sheng Liang
The promise of Large Language Models (LLMs) in Natural Language Processing has often been overshadowed by their limited performance in low-resource languages such as Bangla. To add…
Unleashing the Multilingual Encoder Potential: Boosting Zero-Shot Performance via Probability Calibration
Ercong Nie, Helmut Schmid, Hinrich Schütze
Pretrained multilingual encoder models can directly perform zero-shot multilingual tasks or linguistic probing by reformulating the input examples into cloze-style prompts. This is…
Cross-Lingual Constituency Parsing for Middle High German: A Delexicalized Approach
Ercong Nie, Helmut Schmid, Hinrich Schütze
Constituency parsing plays a fundamental role in advancing natural language processing (NLP) tasks. However, training an automatic syntactic analysis system for ancient languages s…
Baby's CoThought: Leveraging Large Language Models for Enhanced Reasoning in Compact Models
Zheyu Zhang, Han Yang, Bolei Ma +2
Large Language Models (LLMs) demonstrate remarkable performance on a variety of natural language understanding (NLU) tasks, primarily due to their in-context learning ability. This…
Is Prompt-Based Finetuning Always Better than Vanilla Finetuning? Insights from Cross-Lingual Language Understanding
Bolei Ma, Ercong Nie, Helmut Schmid +1
Multilingual pretrained language models (MPLMs) have demonstrated substantial performance improvements in zero-shot cross-lingual transfer across various natural language understan…